We performed a comparison between Amazon Athena and Elastic Search based on real PeerSpot user reviews.
Find out in this report how the two Search as a Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution is very easy to use and integrations are very smooth."
"Amazon Athena is very stable. I never had any issues with it. The dashboarding tool is okay."
"It's easy to set up the product."
"One of the most valuable features is the ability to partition your databases. I also like the federal query functionality, for cases when you have to query outside your S3 storage, or even completely outside of the AWS platform."
"Athena has a really good UI and is very compatible with on-prem products."
"You can perform SQL queries in S3 using Athena."
"The solution has great scalability."
"The most valuable feature for us is the analytics that we can configure and view using Kibana."
"I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product."
"The initial installation and setup were straightforward."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"It is easy to scale with the cluster node model."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"The solution should include a better API for query services."
"If you compare it with Palantir, if you have some data and you want to quickly have a look at it, then that feature is not available in Amazon Cloud."
"One improvement I can suggest is that Athena needs to work better with third-parties. For example, the process of querying a Microsoft SQL warehouse could be improved."
"I would like to use Spark or Python-based queries in Athena."
"I think it would be better if the product were more mature. It's still a young product compared to Power BI or Qlik. I find that development is a bit difficult, but it might be because I'm used to other tools. The dashboarding capabilities could be better. The reporting and statement generation could be better. I couldn't technically initiate picture-perfect reporting, for example, to send out statements every month for banking customers."
"You have to build out the metadata yourself because of the nature of the cloud."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff. They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"Dashboards could be more flexible, and it would be nice to provide more drill-down capabilities."
"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."
Amazon Athena is ranked 4th in Search as a Service with 6 reviews while Elastic Search is ranked 1st in Search as a Service with 59 reviews. Amazon Athena is rated 7.6, while Elastic Search is rated 8.2. The top reviewer of Amazon Athena writes "A great AWS application that is easy to set up and simple to expand". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". Amazon Athena is most compared with Amazon Elasticsearch Service, Amazon AWS CloudSearch and Azure Search, whereas Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Splunk User Behavior Analytics. See our Amazon Athena vs. Elastic Search report.
See our list of best Search as a Service vendors.
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